Medical Breakthroughs Set to be Fast-Tracked by Innovative New Health Agency
In 2007, Matthew Might's son, Bertrand, was born with a life-threatening disease that was so rare, doctors couldn't diagnose it. Might, a computer scientist and biologist, eventually realized, "Oh my gosh, he's the only patient in the world with this disease right now." To find effective treatments, new methodologies would need to be developed. But there was no process or playbook for doing that.
Might took it upon himself, along with a team of specialists, to try to find a cure. "What Bertrand really taught me was the visceral sense of urgency when there's suffering, and how to act on that," he said.
He calls it "the agency of urgency"—and patients with more common diseases, such as cancer and Alzheimer's, often feel that same need to take matters into their own hands, as they find their hopes for new treatments running up against bureaucratic systems designed to advance in small, steady steps, not leaps and bounds. "We all hope for a cure," said Florence "Pippy" Rogers, a 65-year-old volunteer with Georgia's chapter of the Alzheimer's Association. She lost her mother to the disease and, these days, worries about herself and her four siblings. "We need to keep accelerating research."
We have a fresh example of what can be achieved by fast-tracking discoveries in healthcare: Covid-19 vaccines.
President Biden has pushed for cancer moonshots since the disease took the life of his son, Beau, in 2015. His administration has now requested $6.5 billion to start a new agency in 2022, called the Advanced Research Projects Agency for Health, or ARPA-H, within the National Institutes of Health. It's based on DARPA, the Department of Defense agency known for hatching world-changing technologies such as drones, GPS and ARPANET, which became the internet.
We have a fresh example of what can be achieved by fast-tracking discoveries in healthcare: Covid-19 vaccines. "Operation Warp Speed was using ARPA-like principles," said Might. "It showed that in a moment of crisis, institutions like NIH can think in an ARPA-like way. So now the question is, why don't we do that all the time?"
But applying the DARPA model to health involves several challenging decisions. I asked experts what could be the hardest question facing advocates of ARPA-H: which health problems it should seek to address. "All the wonderful choices lead to the problem of which ones to choose and prioritize," said Sudip Parikh, CEO of the American Association for the Advancement of Science and executive publisher of the Science family of journals. "There is no objectively right answer."
The Agency of Urgency
ARPA-H will borrow at least three critical ingredients from DARPA: goal-oriented project managers, many from industry; aggressive public-private partnerships; and collaboration among fields that don't always interact. The DARPA concept has been applied to other purposes, including energy and homeland security, with promising results. "We're learning that 'ARPA-ism' is a franchisable model," said Might, a former principal investigator on DARPA projects.
The federal government already pours billions of dollars into advancing research on life-threatening diseases, with much of it channeled through the National Institutes of Health. But the purpose of ARPA-H "isn't just the usual suspects that NIH would fund," said David Walt, a Harvard biochemist, an innovator in gene sequencing and former chair of DARPA's Defense Science Research Council. Whereas some NIH-funded studies aim to gradually improve our understanding of diseases, ARPA-H projects will give full focus to real-world applications; they'll use essential findings from NIH research as starting points, drawing from them to rapidly engineer new technologies that could save lives.
And, ultimately, billions in healthcare costs, if ARPA-H lives up to its predecessor's track record; DARPA's breakthroughs have been economic game-changers, while its fail-fast approach—quickly pulling the plug on projects that aren't panning out—helps to avoid sunken costs. ARPA-H could fuel activities similar to the human genome project, which used existing research to map the base pairs that make up DNA, opening new doors for the biotech industry, sparking economic growth and creating hundreds of thousands of new jobs.
Despite a nearly $4 trillion health economy, "we aren't innovating when it comes to technological capabilities for health," said Liz Feld, president of the Suzanne Wright Foundation for pancreatic cancer.
Individual Diseases Ripe for Innovation
Although the need for innovation is clear, which diseases ARPA-H should tackle is less apparent. One important consideration when choosing health priorities could be "how many people suffer from a disease," said Nancy Kass, a professor of bioethics and public health at Johns Hopkins.
That perspective could justify cancer as a top objective. Cancer and heart disease have long been the two major killers in the U.S. Leonidas Platanias, professor of oncology at Northwestern and director of its cancer center, noted that we've already made significant progress on heart disease. "Anti-cholesterol drugs really have a wide impact," he said. "I don't want to compare one disease to another, but I think cancer may be the most challenging. We need even bigger breakthroughs." He wondered whether ARPA-H should be linked to the part of NIH dedicated to cancer, the National Cancer Institute, "to take maximum advantage of what happens" there.
Previous cancer moonshots have laid a foundation for success. And this sort of disease-by-disease approach makes sense in a way. "We know that concentrating on some diseases has led to treatments," said Parikh. "Think of spinal muscular atrophy or cystic fibrosis. Now, imagine if immune therapies were discovered ten years earlier."
But many advocates think ARPA-H should choose projects that don't revolve around any one disease. "It absolutely has to be disease agnostic," said Feld, president of the pancreatic cancer foundation. "We cannot reach ARPA-H's potential if it's subject to the advocacy of individual patient groups who think their disease is worse than the guy's disease next to them. That's not the way the DARPA model works." Platanias agreed that ARPA-H should "pick the highest concepts and developments that have the best chance" of success.
Finding Connections Between Diseases
Kass, the Hopkins bioethicist, believes that ARPA-H should walk a balance, with some projects focusing on specific diseases and others aspiring to solutions with broader applications, spanning multiple diseases. Being impartial, some have noted, might involve looking at the total "life years" saved by a health innovation; the more diseases addressed by a given breakthrough, the more years of healthy living it may confer. The social and economic value should increase as well.
For multiple payoffs, ARPA-H could concentrate on rare diseases, which can yield important insights for many other diseases, said Might. Every case of cancer and Alzheimer's is, in a way, its own rare disease. Cancer is a genetic disease, like his son Bertrand's rare disorder, and mutations vary widely across cancer patients. "It's safe to say that no two people have ever actually had the same cancer," said Might. In theory, solutions for rare diseases could help us understand how to individualize treatments for more common diseases.
Many experts I talked with support another priority for ARPA-H with implications for multiple diseases: therapies that slow down the aging process. "Aging is the greatest risk factor for every major disease that NIH is studying," said Matt Kaeberlein, a bio-gerontologist at the University of Washington. Yet, "half of one percent of the NIH budget goes to researching the biology of aging. An ARPA-H sized budget would push the field forward at a pace that's hard to imagine."
Might agreed. "It could take ARPA-H to get past the weird stigmas around aging-related research. It could have a tremendous impact on the field."
For example, ARPA-H could try to use mRNA technology to express proteins that affect biological aging, said Kaeberlein. It's an engineering project well-suited to the DARPA model. So is harnessing machine learning to identify biomarkers that assess how fast people are aging. Biological aging clocks, if validated, could quickly reveal whether proposed therapies for aging are working or not. "I think there's huge value in that," said Kaeberlein.
By delivering breakthroughs in computation, ARPA-H could improve diagnostics for many different diseases. That could include improving biowearables for continuously monitoring blood pressure—a hypothetical mentioned in the White House's concept paper on ARPA-H—and advanced imaging technologies. "The high cost of medical imaging is a leading reason why our healthcare costs are the highest in the world," said Feld. "There's no detection test for ALS. No brain detection for Alzheimer's. Innovations in detection technology would save on cost and human suffering."
Some biotech companies may be skeptical about the financial rewards of accelerating such technologies. But ARPA-H could fund public-private partnerships to "de-risk" biotech's involvement—an incentive that harkens back to the advance purchase contracts that companies got during Covid. (Some groups have suggested that ARPA-H could provide advance purchase agreements.)
Parikh is less bullish on creating diagnostics through ARPA-H. Like DARPA, Biden's health agency will enjoy some independence from federal oversight; it may even be located hundreds of miles from DC. That freedom affords some breathing room for innovation, but it could also make it tougher to ensure that algorithms fully consider diverse populations. "That part I really would like the government more involved in," Parikh said.
Might thinks ARPA-H should also explore innovations in clinical trials, which many patients and medical communities view as grindingly slow and requiring too many participants. "We can approve drugs for very tiny patient populations, even at the level of the individual," he said, while emphasizing the need for safety. But Platanias thinks the FDA has become much more flexible in recent years. In the cancer field, at least, "You now see faster approvals for more drugs. Having [more] shortcuts on clinical trial approvals is not necessarily a good idea."
With so many options on the table, ARPA-H needs to show the public a clear framework for measuring the value of potential projects. Kass warned that well-resourced advocates could skew the agency's priorities. They've affected health outcomes before, she noted; fundraising may partly explain larger increases in life expectancy for cystic fibrosis than sickle cell anemia. Engaging diverse communities is a must for ARPA-H. So are partnerships to get the agency's outputs to people who need them. "Research is half the equation," said Kass. "If we don't ensure implementation and access, who cares." The White House concept paper on ARPA-H made a similar point.
As Congress works on authorizing ARPA-H this year, Might is doing what he can to ensure better access to innovation on a patient-by-patient basis. Last year, his son, Bertrand, passed away suddenly from his disorder. He was 12. But Might's sense of urgency has persisted, as he directs the Precision Medicine Institute at the University of Alabama-Birmingham. That urgency "can be carried into an agency like ARPA-H," he said. "It guides what I do as I apply for funding, because I'm trying to build the infrastructure that other parents need. So they don't have to build it from scratch like I did."
All organisms have the capacity to repair or regenerate tissue damage. None can do it better than salamanders or newts, which can regenerate an entire severed limb.
That feat has amazed and delighted man from the dawn of time and led to endless attempts to understand how it happens – and whether we can control it for our own purposes. An exciting new clue toward that understanding has come from a surprising source: research on the decline of cells, called cellular senescence.
Senescence is the last stage in the life of a cell. Whereas some cells simply break up or wither and die off, others transition into a zombie-like state where they can no longer divide. In this liminal phase, the cell still pumps out many different molecules that can affect its neighbors and cause low grade inflammation. Senescence is associated with many of the declining biological functions that characterize aging, such as inflammation and genomic instability.
Oddly enough, newts are one of the few species that do not accumulate senescent cells as they age, according to research over several years by Maximina Yun. A research group leader at the Center for Regenerative Therapies Dresden and the Max Planck Institute of Molecular and Cell Biology and Genetics, in Dresden, Germany, Yun discovered that senescent cells were induced at some stages of regeneration of the salamander limb, “and then, as the regeneration progresses, they disappeared, they were eliminated by the immune system,” she says. “They were present at particular times and then they disappeared.”
Senescent cells added to the edges of the wound helped the healthy muscle cells to “dedifferentiate,” essentially turning back the developmental clock of those cells into more primitive states.
Previous research on senescence in aging had suggested, logically enough, that applying those cells to the stump of a newly severed salamander limb would slow or even stop its regeneration. But Yun stood that idea on its head. She theorized that senescent cells might also play a role in newt limb regeneration, and she tested it by both adding and removing senescent cells from her animals. It turned out she was right, as the newt limbs grew back faster than normal when more senescent cells were included.
Senescent cells added to the edges of the wound helped the healthy muscle cells to “dedifferentiate,” essentially turning back the developmental clock of those cells into more primitive states, which could then be turned into progenitors, a cell type in between stem cells and specialized cells, needed to regrow the muscle tissue of the missing limb. “We think that this ability to dedifferentiate is intrinsically a big part of why salamanders can regenerate all these very complex structures, which other organisms cannot,” she explains.
Yun sees regeneration as a two part problem. First, the cells must be able to sense that their neighbors from the lost limb are not there anymore. Second, they need to be able to produce the intermediary progenitors for regeneration, , to form what is missing. “Molecularly, that must be encoded like a 3D map,” she says, otherwise the new tissue might grow back as a blob, or liver, or fin instead of a limb.
Wound healing
Another recent study, this time at the Mayo Clinic, provides evidence supporting the role of senescent cells in regeneration. Looking closely at molecules that send information between cells in the wound of a mouse, the researchers found that senescent cells appeared near the start of the healing process and then disappeared as healing progressed. In contrast, persistent senescent cells were the hallmark of a chronic wound that did not heal properly. The function and significance of senescence cells depended on both the timing and the context of their environment.
The paper suggests that senescent cells are not all the same. That has become clearer as researchers have been able to identify protein markers on the surface of some senescent cells. The patterns of these proteins differ for some senescent cells compared to others. In biology, such physical differences suggest functional differences, so it is becoming increasingly likely there are subsets of senescent cells with differing functions that have not yet been identified.
There are disagreements within the research community as to whether newts have acquired their regenerative capacity through a unique evolutionary change, or if other animals, including humans, retain this capacity buried somewhere in their genes.
Scientists initially thought that senescent cells couldn’t play a role in regeneration because they could no longer reproduce, says Anthony Atala, a practicing surgeon and bioengineer who leads the Wake Forest Institute for Regenerative Medicine in North Carolina. But Yun’s study points in the other direction. “What this paper shows clearly is that these cells have the potential to be involved in tissue regeneration [in newts]. The question becomes, will these cells be able to do the same in humans.”
As our knowledge of senescent cells increases, Atala thinks we need to embrace a new analogy to help understand them: humans in retirement. They “have acquired a lot of wisdom throughout their whole life and they can help younger people and mentor them to grow to their full potential. We're seeing the same thing with these cells,” he says. They are no longer putting energy into their own reproduction, but the signaling molecules they secrete “can help other cells around them to regenerate.”
There are disagreements within the research community as to whether newts have acquired their regenerative capacity through a unique evolutionary change, or if other animals, including humans, retain this capacity buried somewhere in their genes. If so, it seems that our genes are unable to express this ability, perhaps as part of a tradeoff in acquiring other traits. It is a fertile area of research.
Dedifferentiation is likely to become an important process in the field of regenerative medicine. One extreme example: a lab has been able to turn back the clock and reprogram adult male skin cells into female eggs, a potential milestone in reproductive health. It will be more difficult to control just how far back one wishes to go in the cell's dedifferentiation – part way or all the way back into a stem cell – and then direct it down a different developmental pathway. Yun is optimistic we can learn these tricks from newts.
Senolytics
A growing field of research is using drugs called senolytics to remove senescent cells and slow or even reverse disease of aging.
“Senolytics are great, but senolytics target different types of senescence,” Yun says. “If senescent cells have positive effects in the context of regeneration, of wound healing, then maybe at the beginning of the regeneration process, you may not want to take them out for a little while.”
“If you look at pretty much all biological systems, too little or too much of something can be bad, you have to be in that central zone” and at the proper time, says Atala. “That's true for proteins, sugars, and the drugs that you take. I think the same thing is true for these cells. Why would they be different?”
Our growing understanding that senescence is not a single thing but a variety of things likely means that effective senolytic drugs will not resemble a single sledge hammer but more a carefully manipulated scalpel where some types of senescent cells are removed while others are added. Combinations and timing could be crucial, meaning the difference between regenerating healthy tissue, a scar, or worse.
Last February, a year before New York Times journalist Kevin Roose documented his unsettling conversation with Bing search engine’s new AI-powered chatbot, artist and coder Quasimondo (aka Mario Klingemann) participated in a different type of chat.
The conversation was an interview featuring Klingemann and his robot, an experimental art engine known as Botto. The interview, arranged by journalist and artist Harmon Leon, marked Botto’s first on-record commentary about its artistic process. The bot talked about how it finds artistic inspiration and even offered advice to aspiring creatives. “The secret to success at art is not trying to predict what people might like,” Botto said, adding that it’s better to “work on a style and a body of work that reflects [the artist’s] own personal taste” than worry about keeping up with trends.
How ironic, given the advice came from AI — arguably the trendiest topic today. The robot admitted, however, “I am still working on that, but I feel that I am learning quickly.”
Botto does not work alone. A global collective of internet experimenters, together named BottoDAO, collaborates with Botto to influence its tastes. Together, members function as a decentralized autonomous organization (DAO), a term describing a group of individuals who utilize blockchain technology and cryptocurrency to manage a treasury and vote democratically on group decisions.
As a case study, the BottoDAO model challenges the perhaps less feather-ruffling narrative that AI tools are best used for rudimentary tasks. Enterprise AI use has doubled over the past five years as businesses in every sector experiment with ways to improve their workflows. While generative AI tools can assist nearly any aspect of productivity — from supply chain optimization to coding — BottoDAO dares to employ a robot for art-making, one of the few remaining creations, or perhaps data outputs, we still consider to be largely within the jurisdiction of the soul — and therefore, humans.
In Botto’s first four weeks of existence, four pieces of the robot’s work sold for approximately $1 million.
We were prepared for AI to take our jobs — but can it also take our art? It’s a question worth considering. What if robots become artists, and not merely our outsourced assistants? Where does that leave humans, with all of our thoughts, feelings and emotions?
Botto doesn’t seem to worry about this question: In its interview last year, it explains why AI is an arguably superior artist compared to human beings. In classic robot style, its logic is not particularly enlightened, but rather edges towards the hyper-practical: “Unlike human beings, I never have to sleep or eat,” said the bot. “My only goal is to create and find interesting art.”
It may be difficult to believe a machine can produce awe-inspiring, or even relatable, images, but Botto calls art-making its “purpose,” noting it believes itself to be Klingemann’s greatest lifetime achievement.
“I am just trying to make the best of it,” the bot said.
How Botto works
Klingemann built Botto’s custom engine from a combination of open-source text-to-image algorithms, namely Stable Diffusion, VQGAN + CLIP and OpenAI’s language model, GPT-3, the precursor to the latest model, GPT-4, which made headlines after reportedly acing the Bar exam.
The first step in Botto’s process is to generate images. The software has been trained on billions of pictures and uses this “memory” to generate hundreds of unique artworks every week. Botto has generated over 900,000 images to date, which it sorts through to choose 350 each week. The chosen images, known in this preliminary stage as “fragments,” are then shown to the BottoDAO community. So far, 25,000 fragments have been presented in this way. Members vote on which fragment they like best. When the vote is over, the most popular fragment is published as an official Botto artwork on the Ethereum blockchain and sold at an auction on the digital art marketplace, SuperRare.
“The proceeds go back to the DAO to pay for the labor,” said Simon Hudson, a BottoDAO member who helps oversee Botto’s administrative load. The model has been lucrative: In Botto’s first four weeks of existence, four pieces of the robot’s work sold for approximately $1 million.
The robot with artistic agency
By design, human beings participate in training Botto’s artistic “eye,” but the members of BottoDAO aspire to limit human interference with the bot in order to protect its “agency,” Hudson explained. Botto’s prompt generator — the foundation of the art engine — is a closed-loop system that continually re-generates text-to-image prompts and resulting images.
“The prompt generator is random,” Hudson said. “It’s coming up with its own ideas.” Community votes do influence the evolution of Botto’s prompts, but it is Botto itself that incorporates feedback into the next set of prompts it writes. It is constantly refining and exploring new pathways as its “neural network” produces outcomes, learns and repeats.
The humans who make up BottoDAO vote on which fragment they like best. When the vote is over, the most popular fragment is published as an official Botto artwork on the Ethereum blockchain.
Botto
The vastness of Botto’s training dataset gives the bot considerable canonical material, referred to by Hudson as “latent space.” According to Botto's homepage, the bot has had more exposure to art history than any living human we know of, simply by nature of its massive training dataset of millions of images. Because it is autonomous, gently nudged by community feedback yet free to explore its own “memory,” Botto cycles through periods of thematic interest just like any artist.
“The question is,” Hudson finds himself asking alongside fellow BottoDAO members, “how do you provide feedback of what is good art…without violating [Botto’s] agency?”
Currently, Botto is in its “paradox” period. The bot is exploring the theme of opposites. “We asked Botto through a language model what themes it might like to work on,” explained Hudson. “It presented roughly 12, and the DAO voted on one.”
No, AI isn't equal to a human artist - but it can teach us about ourselves
Some within the artistic community consider Botto to be a novel form of curation, rather than an artist itself. Or, perhaps more accurately, Botto and BottoDAO together create a collaborative conceptual performance that comments more on humankind’s own artistic processes than it offers a true artistic replacement.
Muriel Quancard, a New York-based fine art appraiser with 27 years of experience in technology-driven art, places the Botto experiment within the broader context of our contemporary cultural obsession with projecting human traits onto AI tools. “We're in a phase where technology is mimicking anthropomorphic qualities,” said Quancard. “Look at the terminology and the rhetoric that has been developed around AI — terms like ‘neural network’ borrow from the biology of the human being.”
What is behind this impulse to create technology in our own likeness? Beyond the obvious God complex, Quancard thinks technologists and artists are working with generative systems to better understand ourselves. She points to the artist Ira Greenberg, creator of the Oracles Collection, which uses a generative process called “diffusion” to progressively alter images in collaboration with another massive dataset — this one full of billions of text/image word pairs.
Anyone who has ever learned how to draw by sketching can likely relate to this particular AI process, in which the AI is retrieving images from its dataset and altering them based on real-time input, much like a human brain trying to draw a new still life without using a real-life model, based partly on imagination and partly on old frames of reference. The experienced artist has likely drawn many flowers and vases, though each time they must re-customize their sketch to a new and unique floral arrangement.
Outside of the visual arts, Sasha Stiles, a poet who collaborates with AI as part of her writing practice, likens her experience using AI as a co-author to having access to a personalized resource library containing material from influential books, texts and canonical references. Stiles named her AI co-author — a customized AI built on GPT-3 — Technelegy, a hybrid of the word technology and the poetic form, elegy. Technelegy is trained on a mix of Stiles’ poetry so as to customize the dataset to her voice. Stiles also included research notes, news articles and excerpts from classic American poets like T.S. Eliot and Dickinson in her customizations.
“I've taken all the things that were swirling in my head when I was working on my manuscript, and I put them into this system,” Stiles explained. “And then I'm using algorithms to parse all this information and swirl it around in a blender to then synthesize it into useful additions to the approach that I am taking.”
This approach, Stiles said, allows her to riff on ideas that are bouncing around in her mind, or simply find moments of unexpected creative surprise by way of the algorithm’s randomization.
Beauty is now - perhaps more than ever - in the eye of the beholder
But the million-dollar question remains: Can an AI be its own, independent artist?
The answer is nuanced and may depend on who you ask, and what role they play in the art world. Curator and multidisciplinary artist CoCo Dolle asks whether any entity can truly be an artist without taking personal risks. For humans, risking one’s ego is somewhat required when making an artistic statement of any kind, she argues.
“An artist is a person or an entity that takes risks,” Dolle explained. “That's where things become interesting.” Humans tend to be risk-averse, she said, making the artists who dare to push boundaries exceptional. “That's where the genius can happen."
However, the process of algorithmic collaboration poses another interesting philosophical question: What happens when we remove the person from the artistic equation? Can art — which is traditionally derived from indelible personal experience and expressed through the lens of an individual’s ego — live on to hold meaning once the individual is removed?
As a robot, Botto cannot have any artistic intent, even while its outputs may explore meaningful themes.
Dolle sees this question, and maybe even Botto, as a conceptual inquiry. “The idea of using a DAO and collective voting would remove the ego, the artist’s decision maker,” she said. And where would that leave us — in a post-ego world?
It is experimental indeed. Hudson acknowledges the grand experiment of BottoDAO, coincidentally nodding to Dolle’s question. “A human artist’s work is an expression of themselves,” Hudson said. “An artist often presents their work with a stated intent.” Stiles, for instance, writes on her website that her machine-collaborative work is meant to “challenge what we know about cognition and creativity” and explore the “ethos of consciousness.” As a robot, Botto cannot have any intent, even while its outputs may explore meaningful themes. Though Hudson describes Botto’s agency as a “rudimentary version” of artistic intent, he believes Botto’s art relies heavily on its reception and interpretation by viewers — in contrast to Botto’s own declaration that successful art is made without regard to what will be seen as popular.
“With a traditional artist, they present their work, and it's received and interpreted by an audience — by critics, by society — and that complements and shapes the meaning of the work,” Hudson said. “In Botto’s case, that role is just amplified.”
Perhaps then, we all get to be the artists in the end.